77 lines
2.2 KiB
C++
77 lines
2.2 KiB
C++
// sherpa-onnx/csrc/offline-tts-vits-impl.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_IMPL_H_
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#define SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_IMPL_H_
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#include <memory>
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#include <string>
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#include <utility>
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#include <vector>
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#include "sherpa-onnx/csrc/lexicon.h"
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#include "sherpa-onnx/csrc/macros.h"
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#include "sherpa-onnx/csrc/offline-tts-impl.h"
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#include "sherpa-onnx/csrc/offline-tts-vits-model.h"
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namespace sherpa_onnx {
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class OfflineTtsVitsImpl : public OfflineTtsImpl {
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public:
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explicit OfflineTtsVitsImpl(const OfflineTtsConfig &config)
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: model_(std::make_unique<OfflineTtsVitsModel>(config.model)),
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lexicon_(config.model.vits.lexicon, config.model.vits.tokens,
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model_->Punctuations()) {}
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GeneratedAudio Generate(const std::string &text,
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int64_t sid = 0) const override {
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std::vector<int64_t> x = lexicon_.ConvertTextToTokenIds(text);
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if (x.empty()) {
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SHERPA_ONNX_LOGE("Failed to convert %s to token IDs", text.c_str());
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return {};
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}
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if (model_->AddBlank()) {
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std::vector<int64_t> buffer(x.size() * 2 + 1);
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int32_t i = 1;
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for (auto k : x) {
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buffer[i] = k;
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i += 2;
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}
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x = std::move(buffer);
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}
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auto memory_info =
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Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
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std::array<int64_t, 2> x_shape = {1, static_cast<int32_t>(x.size())};
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Ort::Value x_tensor = Ort::Value::CreateTensor(
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memory_info, x.data(), x.size(), x_shape.data(), x_shape.size());
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Ort::Value audio = model_->Run(std::move(x_tensor), sid);
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std::vector<int64_t> audio_shape =
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audio.GetTensorTypeAndShapeInfo().GetShape();
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int64_t total = 1;
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// The output shape may be (1, 1, total) or (1, total) or (total,)
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for (auto i : audio_shape) {
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total *= i;
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}
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const float *p = audio.GetTensorData<float>();
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GeneratedAudio ans;
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ans.sample_rate = model_->SampleRate();
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ans.samples = std::vector<float>(p, p + total);
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return ans;
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}
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private:
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std::unique_ptr<OfflineTtsVitsModel> model_;
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Lexicon lexicon_;
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};
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_OFFLINE_TTS_VITS_IMPL_H_
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